[fix] fix pre commit

Author: kew6688

docs/compatibility.md

@@ -10,4 +10,3 @@ The training pipeline now uses the new key name:
 - `instruction_text` → `task`
 
 The updated conversion logic is **not compatible** with InternData-N1 `v0.1`.
-

internnav/dataset/cma_lerobot_dataset.py

@@ -38,7 +38,7 @@ def __init__(
         self.camera_name = self.config.il.camera_name
 
         self.lerobot_as_lmdb = LerobotAsLmdb(self.lerobot_features_dir)
-        self.lmdb_keys = self.lerobot_as_lmdb.get_all_keys(allow_scan_list=['r2r']) # r2r / r2r_aliengo / r2r_flash
+        self.lmdb_keys = self.lerobot_as_lmdb.get_all_keys(allow_scan_list=['r2r'])  # r2r / r2r_aliengo / r2r_flash
         self.length = len(self.lmdb_keys)
         print(f"total keys in traj_data: {len(self.lmdb_keys)}")
 
@@ -106,14 +106,12 @@ def _load_next(self):
                         data['camera_info'][self.camera_name]['rgb'] = data['camera_info'][self.camera_name]['rgb'][
                             :-drop_last_frame_nums
                         ]
-                        data['camera_info'][self.camera_name]['depth'] = data['camera_info'][self.camera_name][
-                            'depth'
-                        ][:-drop_last_frame_nums]
-                        data['robot_info']['yaw'] = data['robot_info']['yaw'][:-drop_last_frame_nums]
-                        data['robot_info']['position'] = data['robot_info']['position'][:-drop_last_frame_nums]
-                        data['robot_info']['orientation'] = data['robot_info']['orientation'][
+                        data['camera_info'][self.camera_name]['depth'] = data['camera_info'][self.camera_name]['depth'][
                             :-drop_last_frame_nums
                         ]
+                        data['robot_info']['yaw'] = data['robot_info']['yaw'][:-drop_last_frame_nums]
+                        data['robot_info']['position'] = data['robot_info']['position'][:-drop_last_frame_nums]
+                        data['robot_info']['orientation'] = data['robot_info']['orientation'][:-drop_last_frame_nums]
                         data['progress'] = data['progress'][:-drop_last_frame_nums]
                         data['step'] = data['step'][:-drop_last_frame_nums]
                         if 'rgb_features' in data.keys():
@@ -133,13 +131,11 @@ def _load_next(self):
 
                     if self.bert_tokenizer is not None:
                         instructions = [
-                            episodes_in_json[ep_idx]['instruction_text']
-                            for ep_idx in range(len(episodes_in_json))
+                            episodes_in_json[ep_idx]['instruction_text'] for ep_idx in range(len(episodes_in_json))
                         ]
                     else:
                         instructions = [
-                            episodes_in_json[ep_idx]['instruction_tokens']
-                            for ep_idx in range(len(episodes_in_json))
+                            episodes_in_json[ep_idx]['instruction_tokens'] for ep_idx in range(len(episodes_in_json))
                         ]
                     for instruction in instructions:
                         new_data = self._create_new_data(data, yaws, instruction)

internnav/dataset/rdp_lerobot_dataset.py

@@ -103,7 +103,7 @@ def __init__(
         self.to_pil = ToPILImage()
         self.image_processor = _transform(n_px=224)  # copy from clip-long
         self.lerobot_as_lmdb = LerobotAsLmdb(self.lerobot_features_dir)
-        self.lmdb_keys = self.lerobot_as_lmdb.get_all_keys(allow_scan_list=['r2r']) # r2r / r2r_aliengo / r2r_flash
+        self.lmdb_keys = self.lerobot_as_lmdb.get_all_keys(allow_scan_list=['r2r'])  # r2r / r2r_aliengo / r2r_flash
         self.length = len(self.lmdb_keys)
         print(f"total keys in traj_data: {len(self.lmdb_keys)}")
 

internnav/habitat_extensions/vln/habitat_vln_evaluator.py

@@ -107,9 +107,7 @@ def __init__(self, cfg: EvalCfg):
         # ------------------------------------- model ------------------------------------------
         self.model_args = argparse.Namespace(**cfg.agent.model_settings)
         self.vis_debug = bool(getattr(self.model_args, "vis_debug", False))
-        self.vis_debug_path = getattr(
-            self.model_args, "vis_debug_path", os.path.join(self.output_path, "vis_debug")
-        )
+        self.vis_debug_path = getattr(self.model_args, "vis_debug_path", os.path.join(self.output_path, "vis_debug"))
 
         processor = AutoProcessor.from_pretrained(self.model_args.model_path)
         processor.tokenizer.padding_side = 'left'
@@ -261,7 +259,7 @@ def resume_from_output_path(self) -> None:
                         ndtw.append(res['ndtw'])
         return sucs, spls, oss, nes, ndtw
 
-    def _run_eval_dual_system(self) -> tuple:
+    def _run_eval_dual_system(self) -> tuple:  # noqa: C901
         self.model.eval()
 
         # resume from previous results
@@ -554,9 +552,7 @@ def _run_eval_dual_system(self) -> tuple:
                     )
                     if pixel_goal is not None:
                         if draw_pixel_goal:
-                            cv2.circle(
-                                vis, (pixel_goal[0], pixel_goal[1]), radius=8, color=(255, 0, 0), thickness=-1
-                            )
+                            cv2.circle(vis, (pixel_goal[0], pixel_goal[1]), radius=8, color=(255, 0, 0), thickness=-1)
                     vis_writer.append_data(vis)
 
                 if action == action_code.LOOKDOWN: